def testCompatV1APIInstrumenting(self):
self.assertFalse(
module_wrapper.TFModuleWrapper.compat_v1_usage_recorded)
apis = {'cosh': ('', 'cmd')}
mock_tf = MockModule('tensorflow')
mock_tf_wrapped = module_wrapper.TFModuleWrapper(mock_tf,
'test',
public_apis=apis)
mock_tf_wrapped.cosh # pylint: disable=pointless-statement
self.assertFalse(
module_wrapper.TFModuleWrapper.compat_v1_usage_recorded)
mock_tf_v1 = MockModule('tensorflow.compat.v1')
mock_tf_v1_wrapped = module_wrapper.TFModuleWrapper(mock_tf_v1,
'test',
public_apis=apis)
self.assertFalse(
module_wrapper.TFModuleWrapper.compat_v1_usage_recorded)
mock_tf_v1_wrapped.cosh # pylint: disable=pointless-statement
self.assertTrue(
module_wrapper.TFModuleWrapper.compat_v1_usage_recorded)
# 'Reset' the status before testing against 'tensorflow.compat.v2.compat.v1'
module_wrapper.TFModuleWrapper.compat_v1_usage_recorded = False
mock_tf_v2_v1 = mock_tf_v1 = MockModule(
'tensorflow.compat.v2.compat.v1')
mock_tf_v2_v1_wrapped = module_wrapper.TFModuleWrapper(
mock_tf_v2_v1, 'test', public_apis=apis)
self.assertFalse(
module_wrapper.TFModuleWrapper.compat_v1_usage_recorded)
mock_tf_v2_v1_wrapped.cosh # pylint: disable=pointless-statement
self.assertTrue(
module_wrapper.TFModuleWrapper.compat_v1_usage_recorded)
def testLazyLoadCorrectLiteModule(self):
# If set, always load lite module from public API list.
module = MockModule('test')
apis = {'lite': ('', 'cmd')}
module.lite = 5
import cmd as _cmd # pylint: disable=g-import-not-at-top
wrapped_module = module_wrapper.TFModuleWrapper(
module, 'test', public_apis=apis, deprecation=False, has_lite=True)
self.assertEqual(wrapped_module.lite, _cmd)
def testLazyLoad(self):
module = MockModule('test')
apis = {'cmd': ('', 'cmd'), 'ABCMeta': ('abc', 'ABCMeta')}
wrapped_module = module_wrapper.TFModuleWrapper(
module, 'test', public_apis=apis, deprecation=False)
import cmd as _cmd # pylint: disable=g-import-not-at-top
from abc import ABCMeta as _ABCMeta # pylint: disable=g-import-not-at-top, g-importing-member
self.assertEqual(wrapped_module.cmd, _cmd)
self.assertEqual(wrapped_module.ABCMeta, _ABCMeta)
def testLazyLoadWildcardImport(self):
# Test that public APIs are in __all__.
module = MockModule('test')
module._should_not_be_public = 5
apis = {'cmd': ('', 'cmd')}
wrapped_module = module_wrapper.TFModuleWrapper(
module, 'test', public_apis=apis, deprecation=False)
setattr(wrapped_module, 'hello', 1)
self.assertIn('hello', wrapped_module.__all__)
self.assertIn('cmd', wrapped_module.__all__)
self.assertNotIn('_should_not_be_public', wrapped_module.__all__)
def testLazyLoadLocalOverride(self):
# Test that we can override and add fields to the wrapped module.
module = MockModule('test')
apis = {'cmd': ('', 'cmd')}
wrapped_module = module_wrapper.TFModuleWrapper(
module, 'test', public_apis=apis, deprecation=False)
import cmd as _cmd # pylint: disable=g-import-not-at-top
self.assertEqual(wrapped_module.cmd, _cmd)
setattr(wrapped_module, 'cmd', 1)
setattr(wrapped_module, 'cgi', 2)
self.assertEqual(wrapped_module.cmd, 1) # override
self.assertEqual(wrapped_module.cgi, 2) # add
def testLazyLoad(self):
module = MockModule('test')
apis = {'cmd': ('', 'cmd'), 'ABCMeta': ('abc', 'ABCMeta')}
wrapped_module = module_wrapper.TFModuleWrapper(
module, 'test', public_apis=apis, deprecation=False)
import cmd as _cmd # pylint: disable=g-import-not-at-top
from abc import ABCMeta as _ABCMeta # pylint: disable=g-import-not-at-top, g-importing-member
self.assertFalse(wrapped_module._fastdict_key_in('cmd'))
self.assertEqual(wrapped_module.cmd, _cmd)
# Verify that the APIs are added to the cache of FastModuleType object
self.assertTrue(wrapped_module._fastdict_key_in('cmd'))
self.assertFalse(wrapped_module._fastdict_key_in('ABCMeta'))
self.assertEqual(wrapped_module.ABCMeta, _ABCMeta)
self.assertTrue(wrapped_module._fastdict_key_in('ABCMeta'))
def _clone_module(m):
"""Shallow clone of module `m`."""
if isinstance(m, _module_wrapper.TFModuleWrapper):
# pylint: disable=protected-access
return _module_wrapper.TFModuleWrapper(
wrapped=_clone_module(m._tfmw_wrapped_module),
module_name=m._tfmw_module_name,
public_apis=m._tfmw_public_apis,
deprecation=m._tfmw_print_deprecation_warnings,
has_lite=m._tfmw_has_lite)
# pylint: enable=protected-access
out = type(m)(m.__name__, m.__doc__)
out.__dict__.update(m.__dict__)
return out
def testLazyLoadDict(self):
# Test that we can override and add fields to the wrapped module.
module = MockModule('test')
apis = {'cmd': ('', 'cmd')}
wrapped_module = module_wrapper.TFModuleWrapper(
module, 'test', public_apis=apis, deprecation=False)
import cmd as _cmd # pylint: disable=g-import-not-at-top
# At first cmd key does not exist in __dict__
self.assertNotIn('cmd', wrapped_module.__dict__)
# After it is referred (lazyloaded), it gets added to __dict__
wrapped_module.cmd # pylint: disable=pointless-statement
self.assertEqual(wrapped_module.__dict__['cmd'], _cmd)
# When we call setattr, it also gets added to __dict__
setattr(wrapped_module, 'cmd2', _cmd)
self.assertEqual(wrapped_module.__dict__['cmd2'], _cmd)
def testLazyLoadLocalOverride(self):
# Test that we can override and add fields to the wrapped module.
module = MockModule('test')
apis = {'cmd': ('', 'cmd')}
wrapped_module = module_wrapper.TFModuleWrapper(
module, 'test', public_apis=apis, deprecation=False)
import cmd as _cmd # pylint: disable=g-import-not-at-top
self.assertEqual(wrapped_module.cmd, _cmd)
setattr(wrapped_module, 'cmd', 1)
setattr(wrapped_module, 'cgi', 2)
self.assertEqual(wrapped_module.cmd, 1) # override
# Verify that the values are also updated in the cache
# of the FastModuleType object
self.assertEqual(wrapped_module._fastdict_get('cmd'), 1)
self.assertEqual(wrapped_module.cgi, 2) # add
self.assertEqual(wrapped_module._fastdict_get('cgi'), 2)
def testDeprecationWarnings(self, mock_warning):
module = MockModule('test')
module.foo = 1
module.bar = 2
module.baz = 3
all_renames_v2.symbol_renames['tf.test.bar'] = 'tf.bar2'
all_renames_v2.symbol_renames['tf.test.baz'] = 'tf.compat.v1.baz'
wrapped_module = module_wrapper.TFModuleWrapper(module, 'test')
self.assertTrue(tf_inspect.ismodule(wrapped_module))
self.assertEqual(0, mock_warning.call_count)
bar = wrapped_module.bar
self.assertEqual(1, mock_warning.call_count)
foo = wrapped_module.foo
self.assertEqual(1, mock_warning.call_count)
baz = wrapped_module.baz # pylint: disable=unused-variable
self.assertEqual(2, mock_warning.call_count)
baz = wrapped_module.baz
self.assertEqual(2, mock_warning.call_count)
# Check that values stayed the same
self.assertEqual(module.foo, foo)
self.assertEqual(module.bar, bar)
from tensorflow.python.ops.check_ops import assert_near_v2 as assert_near
from tensorflow.python.ops.check_ops import assert_negative_v2 as assert_negative
from tensorflow.python.ops.check_ops import assert_non_negative_v2 as assert_non_negative
from tensorflow.python.ops.check_ops import assert_non_positive_v2 as assert_non_positive
from tensorflow.python.ops.check_ops import assert_none_equal_v2 as assert_none_equal
from tensorflow.python.ops.check_ops import assert_positive_v2 as assert_positive
from tensorflow.python.ops.check_ops import assert_proper_iterable
from tensorflow.python.ops.check_ops import assert_rank_at_least_v2 as assert_rank_at_least
from tensorflow.python.ops.check_ops import assert_rank_in_v2 as assert_rank_in
from tensorflow.python.ops.check_ops import assert_rank_v2 as assert_rank
from tensorflow.python.ops.check_ops import assert_same_float_dtype
from tensorflow.python.ops.check_ops import assert_scalar_v2 as assert_scalar
from tensorflow.python.ops.check_ops import assert_shapes_v2 as assert_shapes
from tensorflow.python.ops.check_ops import assert_type_v2 as assert_type
from tensorflow.python.ops.check_ops import is_numeric_tensor
from tensorflow.python.ops.control_flow_ops import Assert
from tensorflow.python.ops.gen_array_ops import check_numerics
from tensorflow.python.ops.numerics import verify_tensor_all_finite_v2 as assert_all_finite
del _print_function
from tensorflow.python.util import module_wrapper as _module_wrapper
if not isinstance(_sys.modules[__name__], _module_wrapper.TFModuleWrapper):
_sys.modules[__name__] = _module_wrapper.TFModuleWrapper(
_sys.modules[__name__],
"debugging",
public_apis=None,
deprecation=False,
has_lite=False)
# This file is MACHINE GENERATED! Do not edit.
# Generated by: tensorflow/python/tools/api/generator/create_python_api.py script.
"""Utility methods to create simple input_fns.
"""
from __future__ import print_function as _print_function
import sys as _sys
from tensorflow_estimator.python.estimator.inputs.numpy_io import numpy_input_fn
from tensorflow_estimator.python.estimator.inputs.pandas_io import pandas_input_fn
del _print_function
from tensorflow.python.util import module_wrapper as _module_wrapper
if not isinstance(_sys.modules[__name__], _module_wrapper.TFModuleWrapper):
_sys.modules[__name__] = _module_wrapper.TFModuleWrapper(
_sys.modules[__name__], "estimator.inputs", public_apis=None, deprecation=True,
has_lite=False)
def testWrapperIsAModule(self):
module = MockModule('test')
wrapped_module = module_wrapper.TFModuleWrapper(module, 'test')
self.assertTrue(tf_inspect.ismodule(wrapped_module))
from tensorflow.python.keras.preprocessing.image import DirectoryIterator
from tensorflow.python.keras.preprocessing.image import ImageDataGenerator
from tensorflow.python.keras.preprocessing.image import Iterator
from tensorflow.python.keras.preprocessing.image import NumpyArrayIterator
from tensorflow.python.keras.preprocessing.image import apply_affine_transform
from tensorflow.python.keras.preprocessing.image import apply_brightness_shift
from tensorflow.python.keras.preprocessing.image import apply_channel_shift
from tensorflow.python.keras.preprocessing.image import array_to_img
from tensorflow.python.keras.preprocessing.image import img_to_array
from tensorflow.python.keras.preprocessing.image import load_img
from tensorflow.python.keras.preprocessing.image import random_brightness
from tensorflow.python.keras.preprocessing.image import random_channel_shift
from tensorflow.python.keras.preprocessing.image import random_rotation
from tensorflow.python.keras.preprocessing.image import random_shear
from tensorflow.python.keras.preprocessing.image import random_shift
from tensorflow.python.keras.preprocessing.image import random_zoom
from tensorflow.python.keras.preprocessing.image import save_img
del _print_function
from tensorflow.python.util import module_wrapper as _module_wrapper
if not isinstance(_sys.modules[__name__], _module_wrapper.TFModuleWrapper):
_sys.modules[__name__] = _module_wrapper.TFModuleWrapper(
_sys.modules[__name__],
"keras.preprocessing.image",
public_apis=None,
deprecation=True,
has_lite=False)
# This file is MACHINE GENERATED! Do not edit.
# Generated by: tensorflow/python/tools/api/generator/create_python_api.py script.
"""Resource management library.
"""
from __future__ import print_function as _print_function
import sys as _sys
from tensorflow.python.platform.resource_loader import get_data_files_path
from tensorflow.python.platform.resource_loader import get_path_to_datafile
from tensorflow.python.platform.resource_loader import get_root_dir_with_all_resources
from tensorflow.python.platform.resource_loader import load_resource
from tensorflow.python.platform.resource_loader import readahead_file_path
del _print_function
from tensorflow.python.util import module_wrapper as _module_wrapper
if not isinstance(_sys.modules[__name__], _module_wrapper.TFModuleWrapper):
_sys.modules[__name__] = _module_wrapper.TFModuleWrapper(
_sys.modules[__name__],
"resource_loader",
public_apis=None,
deprecation=True,
has_lite=False)
from __future__ import print_function as _print_function
import sys as _sys
from tensorflow.python.keras.engine.base_preprocessing_layer import PreprocessingLayer
from tensorflow.python.keras.layers.preprocessing.image_preprocessing import CenterCrop
from tensorflow.python.keras.layers.preprocessing.image_preprocessing import RandomContrast
from tensorflow.python.keras.layers.preprocessing.image_preprocessing import RandomCrop
from tensorflow.python.keras.layers.preprocessing.image_preprocessing import RandomFlip
from tensorflow.python.keras.layers.preprocessing.image_preprocessing import RandomHeight
from tensorflow.python.keras.layers.preprocessing.image_preprocessing import RandomRotation
from tensorflow.python.keras.layers.preprocessing.image_preprocessing import RandomTranslation
from tensorflow.python.keras.layers.preprocessing.image_preprocessing import RandomWidth
from tensorflow.python.keras.layers.preprocessing.image_preprocessing import RandomZoom
from tensorflow.python.keras.layers.preprocessing.image_preprocessing import Rescaling
from tensorflow.python.keras.layers.preprocessing.image_preprocessing import Resizing
from tensorflow.python.keras.layers.preprocessing.normalization_v1 import Normalization
from tensorflow.python.keras.layers.preprocessing.text_vectorization_v1 import TextVectorization
del _print_function
from tensorflow.python.util import module_wrapper as _module_wrapper
if not isinstance(_sys.modules[__name__], _module_wrapper.TFModuleWrapper):
_sys.modules[__name__] = _module_wrapper.TFModuleWrapper(
_sys.modules[__name__],
"keras.layers.experimental.preprocessing",
public_apis=None,
deprecation=True,
has_lite=False)
# This file is MACHINE GENERATED! Do not edit.
# Generated by: tensorflow/python/tools/api/generator/create_python_api.py script.
"""Public API for tf.random.experimental namespace.
"""
from __future__ import print_function as _print_function
import sys as _sys
from tensorflow.python.ops.stateful_random_ops import Generator
from tensorflow.python.ops.stateful_random_ops import create_rng_state
from tensorflow.python.ops.stateful_random_ops import get_global_generator
from tensorflow.python.ops.stateful_random_ops import set_global_generator
del _print_function
from tensorflow.python.util import module_wrapper as _module_wrapper
if not isinstance(_sys.modules[__name__], _module_wrapper.TFModuleWrapper):
_sys.modules[__name__] = _module_wrapper.TFModuleWrapper(
_sys.modules[__name__], "random.experimental", public_apis=None, deprecation=True,
has_lite=False)
"""
from __future__ import print_function as _print_function
import sys as _sys
from tensorflow.python.saved_model.signature_constants import CLASSIFY_INPUTS
from tensorflow.python.saved_model.signature_constants import CLASSIFY_METHOD_NAME
from tensorflow.python.saved_model.signature_constants import CLASSIFY_OUTPUT_CLASSES
from tensorflow.python.saved_model.signature_constants import CLASSIFY_OUTPUT_SCORES
from tensorflow.python.saved_model.signature_constants import DEFAULT_SERVING_SIGNATURE_DEF_KEY
from tensorflow.python.saved_model.signature_constants import PREDICT_INPUTS
from tensorflow.python.saved_model.signature_constants import PREDICT_METHOD_NAME
from tensorflow.python.saved_model.signature_constants import PREDICT_OUTPUTS
from tensorflow.python.saved_model.signature_constants import REGRESS_INPUTS
from tensorflow.python.saved_model.signature_constants import REGRESS_METHOD_NAME
from tensorflow.python.saved_model.signature_constants import REGRESS_OUTPUTS
del _print_function
from tensorflow.python.util import module_wrapper as _module_wrapper
if not isinstance(_sys.modules[__name__], _module_wrapper.TFModuleWrapper):
_sys.modules[__name__] = _module_wrapper.TFModuleWrapper(
_sys.modules[__name__],
"saved_model.signature_constants",
public_apis=None,
deprecation=True,
has_lite=False)
# This file is MACHINE GENERATED! Do not edit.
# Generated by: tensorflow/python/tools/api/generator/create_python_api.py script.
"""Utilities for ImageNet data preprocessing & prediction decoding.
"""
from __future__ import print_function as _print_function
import sys as _sys
from tensorflow.python.keras.applications.imagenet_utils import decode_predictions
from tensorflow.python.keras.applications.imagenet_utils import preprocess_input
del _print_function
from tensorflow.python.util import module_wrapper as _module_wrapper
if not isinstance(_sys.modules[__name__], _module_wrapper.TFModuleWrapper):
_sys.modules[__name__] = _module_wrapper.TFModuleWrapper(
_sys.modules[__name__], "keras.applications.imagenet_utils", public_apis=None, deprecation=True,
has_lite=False)
# This file is MACHINE GENERATED! Do not edit.
# Generated by: tensorflow/python/tools/api/generator/create_python_api.py script.
"""Public API for tf.config.threading namespace.
"""
from __future__ import print_function as _print_function
import sys as _sys
from tensorflow.python.framework.config import get_inter_op_parallelism_threads
from tensorflow.python.framework.config import get_intra_op_parallelism_threads
from tensorflow.python.framework.config import set_inter_op_parallelism_threads
from tensorflow.python.framework.config import set_intra_op_parallelism_threads
del _print_function
from tensorflow.python.util import module_wrapper as _module_wrapper
if not isinstance(_sys.modules[__name__], _module_wrapper.TFModuleWrapper):
_sys.modules[__name__] = _module_wrapper.TFModuleWrapper(
_sys.modules[__name__], "compat.v2.config.threading", public_apis=None, deprecation=False,
has_lite=False)
# This file is MACHINE GENERATED! Do not edit.
# Generated by: tensorflow/python/tools/api/generator/create_python_api.py script.
"""NASNet-A models for Keras.
"""
from __future__ import print_function as _print_function
import sys as _sys
from tensorflow.python.keras.applications import NASNetLarge
from tensorflow.python.keras.applications import NASNetMobile
from tensorflow.python.keras.applications.nasnet import decode_predictions
from tensorflow.python.keras.applications.nasnet import preprocess_input
del _print_function
from tensorflow.python.util import module_wrapper as _module_wrapper
if not isinstance(_sys.modules[__name__], _module_wrapper.TFModuleWrapper):
_sys.modules[__name__] = _module_wrapper.TFModuleWrapper(
_sys.modules[__name__],
"keras.applications.nasnet",
public_apis=None,
deprecation=False,
has_lite=False)
# This file is MACHINE GENERATED! Do not edit.
# Generated by: tensorflow/python/tools/api/generator/create_python_api.py script.
"""Public API for tf.lookup.experimental namespace.
"""
from __future__ import print_function as _print_function
import sys as _sys
from tensorflow.python.ops.lookup_ops import DenseHashTable
del _print_function
from tensorflow.python.util import module_wrapper as _module_wrapper
if not isinstance(_sys.modules[__name__], _module_wrapper.TFModuleWrapper):
_sys.modules[__name__] = _module_wrapper.TFModuleWrapper(
_sys.modules[__name__],
"compat.v2.lookup.experimental",
public_apis=None,
deprecation=False,
has_lite=False)
# This file is MACHINE GENERATED! Do not edit.
# Generated by: tensorflow/python/tools/api/generator/create_python_api.py script.
"""MNIST handwritten digits dataset.
"""
from __future__ import print_function as _print_function
import sys as _sys
from tensorflow.python.keras.datasets.mnist import load_data
del _print_function
from tensorflow.python.util import module_wrapper as _module_wrapper
if not isinstance(_sys.modules[__name__], _module_wrapper.TFModuleWrapper):
_sys.modules[__name__] = _module_wrapper.TFModuleWrapper(
_sys.modules[__name__],
"keras.datasets.mnist",
public_apis=None,
deprecation=False,
has_lite=False)
# This file is MACHINE GENERATED! Do not edit.
# Generated by: tensorflow/python/tools/api/generator/create_python_api.py script.
"""Wrapper for using the Scikit-Learn API with Keras models.
"""
from __future__ import print_function as _print_function
import sys as _sys
from tensorflow.python.keras.wrappers.scikit_learn import KerasClassifier
from tensorflow.python.keras.wrappers.scikit_learn import KerasRegressor
del _print_function
from tensorflow.python.util import module_wrapper as _module_wrapper
if not isinstance(_sys.modules[__name__], _module_wrapper.TFModuleWrapper):
_sys.modules[__name__] = _module_wrapper.TFModuleWrapper(
_sys.modules[__name__],
"keras.wrappers.scikit_learn",
public_apis=None,
deprecation=False,
has_lite=False)
# This file is MACHINE GENERATED! Do not edit.
# Generated by: tensorflow/python/tools/api/generator/create_python_api.py script.
"""Public API for tf.quantization namespace.
"""
from __future__ import print_function as _print_function
import sys as _sys
from tensorflow.python.ops.array_ops import quantize
from tensorflow.python.ops.array_ops import quantize_and_dequantize
from tensorflow.python.ops.gen_array_ops import dequantize
from tensorflow.python.ops.gen_array_ops import fake_quant_with_min_max_args
from tensorflow.python.ops.gen_array_ops import fake_quant_with_min_max_args_gradient
from tensorflow.python.ops.gen_array_ops import fake_quant_with_min_max_vars
from tensorflow.python.ops.gen_array_ops import fake_quant_with_min_max_vars_gradient
from tensorflow.python.ops.gen_array_ops import fake_quant_with_min_max_vars_per_channel
from tensorflow.python.ops.gen_array_ops import fake_quant_with_min_max_vars_per_channel_gradient
from tensorflow.python.ops.gen_array_ops import quantized_concat
del _print_function
from tensorflow.python.util import module_wrapper as _module_wrapper
if not isinstance(_sys.modules[__name__], _module_wrapper.TFModuleWrapper):
_sys.modules[__name__] = _module_wrapper.TFModuleWrapper(
_sys.modules[__name__], "quantization", public_apis=None, deprecation=True,
has_lite=False)
from __future__ import print_function as _print_function
import sys as _sys
from tensorflow.python.keras.constraints import Constraint
from tensorflow.python.keras.constraints import MaxNorm
from tensorflow.python.keras.constraints import MaxNorm as max_norm
from tensorflow.python.keras.constraints import MinMaxNorm
from tensorflow.python.keras.constraints import MinMaxNorm as min_max_norm
from tensorflow.python.keras.constraints import NonNeg
from tensorflow.python.keras.constraints import NonNeg as non_neg
from tensorflow.python.keras.constraints import RadialConstraint
from tensorflow.python.keras.constraints import RadialConstraint as radial_constraint
from tensorflow.python.keras.constraints import UnitNorm
from tensorflow.python.keras.constraints import UnitNorm as unit_norm
from tensorflow.python.keras.constraints import deserialize
from tensorflow.python.keras.constraints import get
from tensorflow.python.keras.constraints import serialize
del _print_function
from tensorflow.python.util import module_wrapper as _module_wrapper
if not isinstance(_sys.modules[__name__], _module_wrapper.TFModuleWrapper):
_sys.modules[__name__] = _module_wrapper.TFModuleWrapper(
_sys.modules[__name__],
"keras.constraints",
public_apis=None,
deprecation=False,
has_lite=False)
from tensorflow.python.keras.layers.pooling import MaxPool2D
from tensorflow.python.keras.layers.pooling import MaxPool2D as MaxPooling2D
from tensorflow.python.keras.layers.pooling import MaxPool3D
from tensorflow.python.keras.layers.pooling import MaxPool3D as MaxPooling3D
from tensorflow.python.keras.layers.recurrent import AbstractRNNCell
from tensorflow.python.keras.layers.recurrent import GRU
from tensorflow.python.keras.layers.recurrent import GRUCell
from tensorflow.python.keras.layers.recurrent import LSTM
from tensorflow.python.keras.layers.recurrent import LSTMCell
from tensorflow.python.keras.layers.recurrent import RNN
from tensorflow.python.keras.layers.recurrent import SimpleRNN
from tensorflow.python.keras.layers.recurrent import SimpleRNNCell
from tensorflow.python.keras.layers.recurrent import StackedRNNCells
from tensorflow.python.keras.layers.serialization import deserialize
from tensorflow.python.keras.layers.serialization import serialize
from tensorflow.python.keras.layers.wrappers import Bidirectional
from tensorflow.python.keras.layers.wrappers import TimeDistributed
from tensorflow.python.keras.layers.wrappers import Wrapper
del _print_function
from tensorflow.python.util import module_wrapper as _module_wrapper
if not isinstance(_sys.modules[__name__], _module_wrapper.TFModuleWrapper):
_sys.modules[__name__] = _module_wrapper.TFModuleWrapper(
_sys.modules[__name__],
"keras.layers",
public_apis=None,
deprecation=True,
has_lite=False)
def testInitCachesAttributes(self):
module = MockModule('test')
wrapped_module = module_wrapper.TFModuleWrapper(module, 'test')
self.assertTrue(wrapped_module._fastdict_key_in('_fastdict_key_in'))
self.assertTrue(wrapped_module._fastdict_key_in('_tfmw_module_name'))
self.assertTrue(wrapped_module._fastdict_key_in('__all__'))
from tensorflow.python.ops.gen_string_ops import decode_base64
from tensorflow.python.ops.gen_string_ops import encode_base64
from tensorflow.python.ops.image_ops_impl import decode_image
from tensorflow.python.ops.image_ops_impl import is_jpeg
from tensorflow.python.ops.parsing_ops import FixedLenFeature
from tensorflow.python.ops.parsing_ops import FixedLenSequenceFeature
from tensorflow.python.ops.parsing_ops import SparseFeature
from tensorflow.python.ops.parsing_ops import VarLenFeature
from tensorflow.python.ops.parsing_ops import decode_csv
from tensorflow.python.ops.parsing_ops import decode_raw_v1 as decode_raw
from tensorflow.python.ops.parsing_ops import parse_example
from tensorflow.python.ops.parsing_ops import parse_sequence_example
from tensorflow.python.ops.parsing_ops import parse_single_example
from tensorflow.python.ops.parsing_ops import parse_single_sequence_example
from tensorflow.python.ops.sparse_ops import deserialize_many_sparse
from tensorflow.python.ops.sparse_ops import serialize_many_sparse
from tensorflow.python.ops.sparse_ops import serialize_sparse
from tensorflow.python.training.input import match_filenames_once
del _print_function
from tensorflow.python.util import module_wrapper as _module_wrapper
if not isinstance(_sys.modules[__name__], _module_wrapper.TFModuleWrapper):
_sys.modules[__name__] = _module_wrapper.TFModuleWrapper(
_sys.modules[__name__],
"compat.v1.io",
public_apis=None,
deprecation=False,
has_lite=False)
def testPickleSubmodule(self): name = PickleTest.__module__ # The current module is a submodule. module = module_wrapper.TFModuleWrapper(MockModule(name), name) restored = pickle.loads(pickle.dumps(module)) self.assertEqual(restored.__name__, name) self.assertIsNotNone(restored.PickleTest)
